Evaluation of effectiveness and safety of the CorPath GRX robotic system in endovascular embolization procedures of cerebral aneurysms
Bibliographic record
Abstract
BACKGROUND: Robotic-assisted neurointervention was recently introduced, with implications that it could be used to treat neurovascular diseases. OBJECTIVE: To evaluate the effectiveness and safety of the robotic-assisted platform CorPath GRX for treating cerebral aneurysms. METHODS: This prospective, international, multicenter study enrolled patients with brain aneurysms that required endovascular coiling and/or stent-assisted coiling. The primary effectiveness endpoint was defined as successful completion of the robotic-assisted endovascular procedure without any unplanned conversion to manual treatment with guidewire or microcatheter navigation, embolization coil(s) or intracranial stent(s) deployment, or an inability to navigate vessel anatomy. The primary safety endpoint included intraprocedural and periprocedural events. RESULTS: The study enrolled 117 patients (74.4% female) with mean age of 56.6 years from 10 international sites,. Headache was the most common presenting symptom in 40/117 (34.2%) subjects. Internal carotid artery was the most common location (34/122, 27.9%), and the mean aneurysm height and neck width were 5.7±2.6 mm and 3.5±1.4 mm, respectively. The overall procedure time was 117.3±47.3 min with 59.4±32.6 min robotic procedure time. Primary effectiveness was achieved in 110/117 (94%) subjects with seven subjects requiring conversion to manual for procedure completion. Only four primary safety events were recorded with two intraprocedural aneurysm ruptures and two strokes. A Raymond-Roy Classification Scale score of 1 was achieved in 71/110 (64.5%) subjects, and all subjects were discharged with a modified Rankin Scale score of ≤2. CONCLUSIONS: This first-of-its-kind robotic-assisted neurovascular trial demonstrates the effectiveness and safety of the CorPath GRX System for endovascular embolization of cerebral aneurysm procedures. TRIAL REGISTRATION NUMBER: NCT04236856.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".